Data Analytics: the new frontier of manufacturing

The technological development of Industry 4.0 and digitalization has shifted the focus to the value of data and the informational content extractable from it: in this sense, Analytics represent one of the tools for qualitative and quantitative analysis aimed at generating information from raw data.

Data Analytics: the new frontier of 4.0 manufacturing. Data and its informational content represent the future of Industry 4.0. Indeed, data is a key factor for increased productivity, improved efficiency, and better utilization and saturation of productive resources.

In recent years, the progressive diffusion of Industrial Internet of Things technologies has enabled the collection and massive storage of large amounts of data – both sensorial and non – measurable and acquirable from the field, overcoming the technical and implementative difficulties that characterized the world of automation prior to Industry 4.0: hence, there is a great wealth of value-added information potentially available to end users.

Apart from the aspects of transmitting and manipulating data flows from the field to the cloud and vice versa, inherent in the world of field industrial communication and related protocols, another equally important factor is the ability to use this raw data to the concrete benefit of the company by performing appropriate analyses and processing to extract potentially significant results and indications.

Hence the tangible evidence of the possible use of so-called “Analytics“, a tool born from the digital transformation of Industry 4.0 aimed at implementing and making available a set of quantitative and qualitative approaches capable of converting raw data into easily interpretable information that can benefit companies.

In particular, the manufacturing industry is beginning to adopt analytics for the analysis of sensor data acquired from the field in real-time, not only to provide decision support tools but also to enable a higher degree of factory automation.

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